This two-day course covers some of the most exciting and current topics within the R community. Although traditionally R has not been used for Big Data analytics due to its memory limitations, recent R packages have provided much-needed connectivity for out-of-memory processing with popular Big Data tools such as Hadoop, Spark, SQL and NoSQL databases etc. During this intense and skills-oriented course you will learn:
to use third-party R packages, which support parallel computing in order to increase the speed and processing capabilities of R,
to work on large data sets in the Cloud (Microsoft Azure and Amazon EC2) through R deployed on the server,
to implement MapReduce framework through Hadoop straight from R console,
to manage Hadoop Distributed File System and HBase database through R,
to connect to and extract, aggregate and manage the data in major relational SQL-based database management systems (RDBMSs) using a variety of R packages,
to apply NoSQL queries to access, transform and manipulate large data sets in MongoDB using R packages,
to improve the data flow and speed of processing of large data sets through R’s connectivity with Spark,
to implement selected Big Data tools in the Big Data Product Cycle with R.
The course will be presented by Simon Walkowiak – a cognitive neuroscientist and an author of “Big Data Analytics with R”. Simon is Mind Project’s expert in Big Data architecture for predictive modelling and has delivered numerous Big Data and Machine Learning training courses at various institutions, financial/business organisations, governmental departments and UK universities (including Big Data & Analytics Summer School organised by the Institute for Analytics and Data Science). He is also a former Data Curator at the UK Data Archive – the largest socio-economic digital data depository in Europe.
The course will run for 2 days from 9:30am until ~5:00pm on each day and will consist of alternating lecture-style presentations and practical tutorials. The example datasets used during tutorial sessions will come from social sciences, economics and business fields, however the contents may vary depending on specific interests of participants (based on the Participant’s Skills Inventory). There will be two 15-minute coffee/tea breaks and one 1-hour lunch break on each day.
What is included?
Apart from the contents of the course, Mind Project will provide the participants with the following:
a digital (USB memory stick) Course Manual including all presentation slides, R course codes and a list of reference books and online resources,
additional home exercises and all data sets available to download,
Central London location – a 1-min walk from the Barbican station, 5 minutes away from Farringdon and St. Paul’s stations, 15 minutes from the Liverpool Street Station,
Mind Project course attendance certificate.
In order to fully benefit from the training course, we recommend that attendees bring their personal laptops to the session with the most recent version of R and RStudio software installed and at least one of the following web browsers: Chrome, Safari, Mozilla Firefox and/or Internet Explorer. As R is a free environment you can download it directly from www.r-project.org website and RStudio is available at https://www.rstudio.com/products/rstudio/#Desktop. Please contact us should you have any questions or issues with the installation process. No specific R packages are required before the course (the course tutors will explain this during the training).
This course is targeted at users with some R experience (preferably at Intermediate level) and interest in Machine Learning algorithms. Our “Applied Data Science in R” training course is a good pre-requisite to participate in this course.
Participants are encouraged to complete the online Participant’s Skills Inventory to allow Mind Project and our course tutors to customise the contents of the course depending on the level of participants’ knowledge and their areas of interest. The data obtained through the Participant’s Skills Inventory will be held fully-confidential and will only be used to provide a quality data analysis training.
Deadline for registrations
The deadline for registrations on this training course is Tuesday, 17th of October 2017 at 16:00 London (UK) time. However, Mind Project reserves the right to end the registration process earlier if all places are booked before the deadline.
Prices and discounts
- £375 + VAT (£450) per person for the whole course (regular fee).
- £250 + VAT (£300) per person for the whole course for UK registered undergraduate and postgraduate students, and representatives of registered charitable organisations (discounted fee).
- For group bookings of 4 and more participants, please contact us directly.
Please mind that the course fee DOES NOT include the following:
- transport to and from the venue,
- accommodation and lunch.
Please contact us should you have any questions about this course. You may also want to visit the Training Courses – Frequently Asked Questions website, which gives further practical details about Mind Project training courses. You can book your place on the course by clicking Book ticket button in the top section of the course page. Please note that we accept all major credit/debit cards (through the PayPal and Stripe systems) and BACS payments. We can only confirm fully-paid bookings. Please contact us for other payment options e.g. if a Purchase Order is required. Please read Training & Events Terms & Conditions before your purchase.
Course feedback and testimonials
We have received the following testimonials for the previous editions of this course:
- “Well presented, the instructor knows his field very well and helped me to understand the relative differences between the technologies available.”
- “Great teacher, excellent pace. Teacher helpful, approachable and knowledgable.”
- “Great course if you want to leverage the power of Big Data combined with the functionality of R.”
Based on the anonymous feedback forms we have also received the following comments from our attendees:
- “Easy to follow – even for a relative beginner in R.”
- “The Virtual Machine setup made it easy to try things out.”
- “I liked the pace and content of the course.”
- “It was great to see so many ways to use Big Data with R.”
The course will be held at CAP House, 1st Floor, 9-12 Long Lane, London, EC1A 9HA. Please see the map below.